Multiplexed representation of others in the hippocampal CA1 subfield of female mice

Hippocampal place cells represent the position of a rodent within an environment. In addition, recent experiments show that the CA1 subfield of a passive observer also represents the position of a conspecific performing a spatial task. However, whether this representation is allocentric, egocentric or mixed is less clear. In this study we investigated the representation of others during free behavior and in a task where female mice learned to follow a conspecific for a reward. We found that most cells represent the position of others relative to self-position (social-vector cells) rather than to the environment, with a prevalence of purely egocentric coding modulated by context and mouse identity. Learning of a pursuit task improved the tuning of social-vector cells, but their number remained invariant. Collectively, our results suggest that the hippocampus flexibly codes the position of others in multiple coordinate systems, albeit favoring the self as a reference point.

a, Scheme of the positions of an imaged mouse and its conspecific (top) and the corresponding extension of spatial maps (bottom) in each coordinate system (columns).
Note that maps for selfPC and socialPC can be thought of as spanning the physical arena, while maps for alloSVC and egoSVC, which code for the position of one mouse relative to the other, need to be considered in an 'effective arena' with a four times larger area.Scale bar: 10 cm.b, Fraction of imaged cells falling into each category (similar to Fig. 1g) but grouping data by mouse (mean ± s.e.m.; n = 18 imaged mice.RM one-way ANOVA, df = 3, F (1.5, 26.2) = 14.04, p = 2.0×10 -4 .Holm-Šídák's multiple comparisons test for each cell type, p value indicated).c, Distance in pixels between pairs of centroids of somas belonging to the same (blue) or to a different (violet) category (median ± i.q.r., Mann Whitney test, two tailed, Mann-Whitney U = 3252835237, Cliff's Delta = -4.4×10 - , p = 0.14).(effectively removing 12 ± 2 % of data from each session).Third, a similar approach but using a cutoff value of 5 cm s -1 (effectively removing 26 ± 3 % of data from each session).
Fourth, selecting only sessions with very homogeneous coverage of head direction by the imaged mouse (mean vector length < 0.1; 5 out of 18 sessions; see b).Fifth, imposing a set of stricter criteria on cell classification: mean event rate above 0.1 Hz and a detectable field of at least 25 spatial bins (5 × 5 bins; side of square bins: 2 cm for selfPCs and socialPCs or 4 cm for alloSVCs and egoSVCs).Sixth: similar stricter criteria but adding a minimum correlation between halves of the session of 0.     a, ANOVA analysis to explain variability in cross-validated decoding error within sessions (pool of 5 unfamiliar and 5 familiar sessions) using familiarity, interaction (whether or not mice were interacting at a given timestamp) and distance between mice as independent variables.b, For data in Fig. 3i, decoding error as a function of distance between mice (mean ± s.e.m.).The improvement in decoding error for unfamiliar mice is explained by the greater amount of time spent at shorter distances.This is consistent with a bias in egoSVC decoding error for mice that are far apart related to purely geometrical reasons.c, Schematic explanation of the bias in egoSVC decoding error for mice that are far apart.
Mice very close to each other in physical space (top, left) have a relative position in the egoSVC effective arena close to the center (bottom, left).In this situation, the maximum error for a decoder is the radius of the effective arena, equal to the diameter of the physical arena.Mice in opposite ends of the physical arena (top, right) have a relative position in the egoSVC effective arena close to the edge (bottom, right).In this situation, the maximum error for a decoder is the diameter of the effective arena, equal to twice the diameter of the physical arena.Source data are provided as a Source Data file.

d,
Figure1 classfication 5. Seventh, considering for each cell type classification only sessions with coverage above 70 %.Eighth, considering only sessions in which coverage was above 70 % for all coordinate systems simultaneously (8 out of 18 sessions; see examples in Supplementary Fig.5b).Ninth, binarizing deconvoluted calcium data with a threshold of 0 instead of 3 standard deviations.Tenth, using deconvolved signals without binarization.Note that the relative proportion of cell types is roughly maintained.b, For all sessions (one per animal; rows) with very homogeneous cover of head direction by the imaged mouse (mean vector length < 0.1), angular distribution of head direction (left subpanel), angular distribution of egoSVC direction (center subpanel) and egoSVC fields (right subpanel).Scale bar: 20 cm.Source data are provided as a Source Data file.
distance explains low decoding error for unfamiliar sessions